A Weighted Subsethood Mamdani Fuzzy Rules Based System Rule Extraction (MFRB-WSBA) for Forecasting Electricity Load Demand - A Framework

Rosnalini Mansor, Maznah Mat Kasim, Mahmod Othman

Abstract


Fuzzy rules are very important elements that should be taken consideration seriously when applying any fuzzy system. This paper proposes the framework of Mamdani Fuzzy Rulebased System with Weighted Subsethood-based Algorithm (MFRBS-WSBA) for forecasting electricity load demand. Specifically, this paper proposed two frameworks: MFRBSWSBA and WSBA framework where the WSBA is embedded in MFRBS-WSBA (fourth step in MFRBS-WSBA). The objective of this paper is to show the fourth step in the MFRBS-WSBA framework which applied the new electricity load forecasting rule extraction by WSBA method. We apply the proposed WSBA framework in Malaysia electricity load demand data as a numerical example in this paper. These preliminary results show that the WSBA framework can be one of alternative methods to extract fuzzy rules for forecast electricity load demand where the proposed method provide a simple to interpret the fuzzy rules and also offer a new direction to interpret the fuzzy rules compared to classical fuzzy rules

Keywords


Fuzzy Rules; Forecasting; Electricity Load Demand;

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ISSN: 2180-1843

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